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Di Zhang

ACL 2026×2ICML 2026效率与系统强化学习与后训练推理
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1 一作 · 3 篇 · ACL 2026 / ICML 2026

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2026 顶会论文

3
一作ACL 2026Poster· Natural Language Processing

Towards Stable and Effective Reinforcement Learning for Mixture-of-Experts

Di Zhang · xun wu · Shaohan Huang · Lingjie Jiang · Yaru Hao · Li Dong · Zewen Chi · Zhifang Sui · Furu Wei

摘要

Reinforcement learning with verifiable rewards (RLVR) has emerged as a powerful paradigm for improving reasoning capabilities. However, training RLVR with Mixture-of-Experts (MoE) policies remains fragile and is often prone to reward collapse.We identify a MoE-specific source of instability, refe...

强化学习与后训练推理效率与系统OpenReview 项目页
作者位次 #4/6ACL 2026Findings· Findings of ACL

S elf B udgeter: Adaptive Token Allocation for Efficient LLM Reasoning

Zheng Li · Qingxiu Dong · Jingyuan Ma · Di Zhang · Kai Jia · Zhifang Sui

摘要

Recently, large reasoning models demonstrate exceptional performance on various tasks. However, reasoning models always consume excessive tokens even for simple queries, leading to resource waste and prolonged user latency. To address this challenge, we propose SelfBudgeter - a self-adaptive reas...

效率与系统推理强化学习与后训练OpenReview 项目页

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